Papers with online machine translation

2 papers
TranslateLocally: Blazing-fast translation running on the local CPU (2021.emnlp-demo)

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Challenge: Using cloud-based translation providers carries privacy risks, as users lose control of their data once it enters the web.
Approach: They propose a desktop translation application that runs locally on a user's desktop or laptop CPU. translateLocally delivers cloud-like translation speed and quality even on 10 year old hardware.
Outcome: The open-source translation system runs on Linux, Windows and macOS on desktops and laptops.
OPUS-CAT: Desktop NMT with CAT integration and local fine-tuning (2021.eacl-demos)

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Challenge: Neural machine translation (NMT) has brought about a dramatic increase in the quality of machine translation in the past five years.
Approach: OPUS-CAT is a collection of software which enables translators to use neural machine translation in computer-assisted translation tools without exposing themselves to security and confidentiality risks.
Outcome: OPUS-CAT is a collection of software which enables translators to use neural machine translation in computer-assisted translation tools without exposing themselves to security and confidentiality risks.

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